Incidence and consequences of damage to insecticide-treated mosquito nets in Kenya

Background Efforts to improve the impact of long-lasting insecticidal nets (LLINs) should be informed by understanding of the causes of decay in effect. Holes in LLINs have been estimated to account for 7–11% of loss in effect on vectorial capacity for Plasmodium falciparum malaria in an analysis of repeated cross-sectional surveys of LLINs in Kenya. This does not account for the effect of holes as a cause of net attrition or non-use, which cannot be measured using only cross-sectional data. There is a need for estimates of how much these indirect effects of physical damage on use and attrition contribute to decay in effectiveness of LLINs. Methods Use, physical integrity, and survival were assessed in a cohort of 4514 LLINs followed for up to 4 years in Kenya. Flow diagrams were used to illustrate how the status of nets, in terms of categories of use, physical integrity, and attrition, changed between surveys carried out at 6-month intervals. A compartment model defined in terms of ordinary differential equations (ODEs) was used to estimate the transition rates between the categories. Effects of physical damage to LLINs on use and attrition were quantified by simulating counterfactuals in which there was no damage. Results Allowing for the direct effect of holes, the effect on use, and the effect on attrition, 18% of the impact on vectorial capacity was estimated to be lost because of damage. The estimated median lifetime of the LLINs was 2.9 years, but this was extended to 5.7 years in the counterfactual without physical damage. Nets that were in use were more likely to be in a damaged state than unused nets but use made little direct difference to LLIN lifetimes. Damage was reported as the reason for attrition for almost half of attrited nets, but the model estimated that almost all attrited nets had suffered some damage before attrition. Conclusions Full quantification of the effects of damage will require measurement of the supply of new nets and of household stocks of unused nets, and also of their impacts on both net use and retention. The timing of mass distribution campaigns is less important than ensuring sufficient supply. In the Kenyan setting, nets acquired damage rapidly once use began and the damage led to rapid attrition. Increasing the robustness of nets could substantially increase their lifetime and impact but the impact of LLIN programmes on malaria transmission is ultimately limited by levels of use. Longitudinal analyses of net integrity data from different settings are needed to determine the importance of physical damage to nets as a driver of attrition and non-use, and the importance of frequent use as a cause of physical damage in different contexts. Supplementary Information The online version contains supplementary material available at 10.1186/s12936-021-03978-7.


Supplementary data description
1 gives a breakdown of the recorded information on the causes of attrition and reasons why nets were absent at the time of survey. Destructively sampled nets are listed under their status prior to being removed to the laboratory.

1
The analysis of reported reasons for attrition considers only nets classified as 'Discarded-Too torn' as reported damage.

Figure S 1. Pairs plot of the Markov Chain Monte Carlo (MCMC) samples for ODE model parameters
The marginal distribution for each parameter is in the main diagonal. The entries above the main diagonal are scatters of paired samples from the posterior distributions. The entries below the main diagonal are the corresponding correlation coefficients. Correlation coefficients with magnitude greater than 0.3 are shown against a gray background.

Sensitivity analyses Methods
The parameters of the ODE models were re-estimated with four distinct definitions of attrition (A1-A4), for different qualifying levels of damage (analysis A1_0), and for different assumptions about nets that were recorded as transitioning from damaged to undamaged (analysis A1_I) (Table S 2, Table S 3). A1 treats absent nets as attrition but nets elsewhere are not considered as attrition; rather they are treated as censored (i.e. having unknown status).
A2 considers as attrition only those nets that were reported as destroyed or repurposed (repurposed nets are included with destroyed nets for the purpose of this analysis). Intervals that ended with the net being sold, given away, or relocated were not included in this analysis (effectively treating such nets as remaining in the cohort. This model was used to estimate , the proportion of destroyed nets that had been damaged before they were destroyed (see section Error! Reference source not found.). This gave the value: = 0.985.
A3 considers as attrition nets that were recorded as elsewhere, in addition to those recorded as destroyed, where elsewhere encompasses sale, giving away, or relocation. This model was used to estimate , the proportion of all these nets that had been damaged before attrition according to this broader definition: The questionnaire responses reported in Error! Reference source not found. provide an estimate of , the proportion elsewhere among absent and destroyed nets, is defined as the proportion of nets elsewhere that were damaged before they were taken away, and can be obtained from simple probability calculations, since: which can be rearranged to give: A4 considers as attrition all nets that were eligible to be followed up but were not present. In addition to destroyed and nets that were elsewhere, this includes nets that were absent for which there was no data, in those cases where the net did not reappear at a subsequent survey. This model was used to estimate , the proportion of all nets that had been damaged before the survey where they did not appear. This gave the value: = 0.834.

Recycling of nets
Treating absent nets as a mixture of destroyed and nets that were elsewhere, the mixing proportion was estimated by assuming the association between holes and the outcome (destruction or removal) to be the same in the absent nets as for those with explicit information about the outcome, and that this can be quantified by the odds ratio: The Markov property of the transition model justifies simulating nets that are elsewhere as returning either to compartment (if they are undamaged), or to compartment (if they are damaged). Recycling of absent nets was simulated using the A1 primary definition of attrition, but at each time, t, returning a proportion of attrition to the forward simulations, where the allocation between compartments and was determined from the proportion of attrition arising from damaged nets, ( ), and the odds ratio, Ψ, where: The allocation between and was determined from the 2 x 2 table classifying the attrition at any given time (Table S 4). Defining as the (time dependent) proportion of attrition that both have holes and will be recycled (to ): So that the model equations (model A1R) become: Where the parameter vector { ℎ , ℎ , , , , , , } is that estimated with the A1 definition of attrition.

Results of sensitivity analyses
With the exception of the parameters measuring attrition rates, the fitted values for the parameter vector were similar for each of the analyses A1-A4, and for A1_0 and A1_I (Table S 5). This was reflected in the derived values given in Table S 6, where substantial differences are seen only in the projected lifetimes of the nets. Simulation A1_0, in which the reference model (A1) was re-fitted, classifying nets with any holes as damaged (rather than requiring a PHI>20) gave very similar results to the original (A1). Similarly, the alternative coding of apparently repaired nets (A1_I), in which these were coded as undamaged at both start and end of the interval, made little difference to the projections from the model (Figure S 2). The alternative definitions of attrition made considerable differences to the model predictions ( Figure  S 3). Analysis A2, which considers only explicitly destruction or repurposing as attrition, suggests a median net lifetime of 9.3 years (Table S 2); conversely, A3 and A4, which have more inclusive definitions of attrition, give rise to simulations with shorter lifetimes. The simulation with recycling (A1R) gives similar results to A2. The definition of attrition made little difference to the simulated proportion of nets in the undamaged states ( Figure S 3), and in all simulations by the age of three years almost all nets are classified as damaged, so the differences between simulations mainly relate to the question of how often damaged nets that are absent, or which are stated to have been moved elsewhere, remain in use.